Triple
T17291371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fali Sam Nariman |
E419791
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Nariman
Nariman is an Indian surname notably borne by Fali Sam Nariman, a prominent jurist and constitutional expert.
|
E1260860
|
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: Nariman | Statement: [Fali Sam Nariman, familyName, Nariman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nariman Context triple: [Fali Sam Nariman, familyName, Nariman]
-
A.
Kinan Azmeh
Kinan Azmeh is a Syrian clarinetist and composer known for blending classical, jazz, and Middle Eastern musical traditions in his performances and compositions.
-
B.
Nasiri
Nasiri is the family name of the ruling house of the Nasiri dynasty, a historical Muslim dynasty.
-
C.
Fatima Namazi
Fatima Namazi is a member of the Office of Special Projects, contributing to its specialized initiatives and operations.
-
D.
Soraya Tarzi
Soraya Tarzi was a pioneering Afghan queen and women's rights advocate in the early 20th century who played a key role in her country’s modernization.
-
E.
Sediqa Massoud
Sediqa Massoud is the widow of famed Afghan resistance leader Ahmad Shah Massoud and a prominent advocate for women's rights and education in Afghanistan.
- 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: Nariman Triple: [Fali Sam Nariman, familyName, Nariman]
Generated description
Nariman is an Indian surname notably borne by Fali Sam Nariman, a prominent jurist and constitutional expert.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nariman Target entity description: Nariman is an Indian surname notably borne by Fali Sam Nariman, a prominent jurist and constitutional expert.
-
A.
Kinan Azmeh
Kinan Azmeh is a Syrian clarinetist and composer known for blending classical, jazz, and Middle Eastern musical traditions in his performances and compositions.
-
B.
Nasiri
Nasiri is the family name of the ruling house of the Nasiri dynasty, a historical Muslim dynasty.
-
C.
Fatima Namazi
Fatima Namazi is a member of the Office of Special Projects, contributing to its specialized initiatives and operations.
-
D.
Soraya Tarzi
Soraya Tarzi was a pioneering Afghan queen and women's rights advocate in the early 20th century who played a key role in her country’s modernization.
-
E.
Sediqa Massoud
Sediqa Massoud is the widow of famed Afghan resistance leader Ahmad Shah Massoud and a prominent advocate for women's rights and education in Afghanistan.
- 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_69d886db32608190a61e18862c5a8af6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e437837d048190949b947f5437636d |
completed | April 19, 2026, 2:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a017959ffb0819099d70ed1541158ee |
completed | May 11, 2026, 6:38 a.m. |
| NEDg | Description generation | batch_6a017c9e99888190a99e3910c46d90c5 |
completed | May 11, 2026, 6:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a017d340b988190a468753604150bd3 |
completed | May 11, 2026, 6:54 a.m. |
Created at: April 10, 2026, 5:40 a.m.