Triple
T1006167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Graham Hancock |
E21716
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Santha Faiia
Santha Faiia is a photographer known for her work documenting ancient sacred sites and for being married to author and researcher Graham Hancock.
|
E130100
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Santha Faiia | Statement: [Graham Hancock, spouse, Santha Faiia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santha Faiia Context triple: [Graham Hancock, spouse, Santha Faiia]
-
A.
Dorla Gondi
Dorla Gondi is a regional dialect of the Gondi language spoken by the Dorla subgroup of the Gondi people in central India.
-
B.
Nita Naldi
Nita Naldi was a prominent American silent film actress best known for her sultry vamp roles opposite stars like Rudolph Valentino in the early 1920s.
-
C.
Amara Namani
Amara Namani is a young, resourceful Jaeger pilot and central protagonist in the science fiction film "Pacific Rim: Uprising."
-
D.
Nabaneeta
Nabaneeta is a feminine given name most notably borne by the acclaimed Indian Bengali writer and academic Nabaneeta Dev Sen.
-
E.
Elizabeth Pomada
Elizabeth Pomada is an American author and historian best known for popularizing San Francisco’s colorful Victorian houses through her influential work on the “Painted Ladies.”
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Santha Faiia Triple: [Graham Hancock, spouse, Santha Faiia]
Generated description
Santha Faiia is a photographer known for her work documenting ancient sacred sites and for being married to author and researcher Graham Hancock.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Santha Faiia Target entity description: Santha Faiia is a photographer known for her work documenting ancient sacred sites and for being married to author and researcher Graham Hancock.
-
A.
Dorla Gondi
Dorla Gondi is a regional dialect of the Gondi language spoken by the Dorla subgroup of the Gondi people in central India.
-
B.
Nita Naldi
Nita Naldi was a prominent American silent film actress best known for her sultry vamp roles opposite stars like Rudolph Valentino in the early 1920s.
-
C.
Amara Namani
Amara Namani is a young, resourceful Jaeger pilot and central protagonist in the science fiction film "Pacific Rim: Uprising."
-
D.
Nabaneeta
Nabaneeta is a feminine given name most notably borne by the acclaimed Indian Bengali writer and academic Nabaneeta Dev Sen.
-
E.
Elizabeth Pomada
Elizabeth Pomada is an American author and historian best known for popularizing San Francisco’s colorful Victorian houses through her influential work on the “Painted Ladies.”
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b51434f081909b301ad1c151af03 |
completed | March 1, 2026, 9:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac5995ad6c8190a324094151442bce |
completed | March 7, 2026, 5 p.m. |
| NEDg | Description generation | batch_69ac5a2cae9881908a9cfc09f9ef0968 |
completed | March 7, 2026, 5:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac5b54d1f881909a367d12647eee3f |
completed | March 7, 2026, 5:07 p.m. |
Created at: March 1, 2026, 7:41 p.m.