Triple
T15927078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The 4400 |
E386229
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Maira Suro
Maira Suro is a television producer best known for her executive production work on the science fiction series "The 4400."
|
E1184845
|
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: Maira Suro | Statement: [The 4400, executiveProducer, Maira Suro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maira Suro Context triple: [The 4400, executiveProducer, Maira Suro]
-
A.
Maira
Maira is a given name used in various cultures, often as a variant of names like Maera, Maria, or Mary.
-
B.
Mona Rudao
Mona Rudao was a Seediq indigenous chieftain and resistance leader in Taiwan who led an uprising against Japanese colonial rule in 1930.
-
C.
Marisa
Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
-
D.
Fairuza
Fairuza is a feminine given name most famously borne by American actress Fairuza Balk.
-
E.
Riza
Riza is a masculine given name commonly used in various cultures, often with roots in Arabic and Turkish languages.
- 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: Maira Suro Triple: [The 4400, executiveProducer, Maira Suro]
Generated description
Maira Suro is a television producer best known for her executive production work on the science fiction series "The 4400."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maira Suro Target entity description: Maira Suro is a television producer best known for her executive production work on the science fiction series "The 4400."
-
A.
Maira
Maira is a given name used in various cultures, often as a variant of names like Maera, Maria, or Mary.
-
B.
Mona Rudao
Mona Rudao was a Seediq indigenous chieftain and resistance leader in Taiwan who led an uprising against Japanese colonial rule in 1930.
-
C.
Marisa
Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
-
D.
Fairuza
Fairuza is a feminine given name most famously borne by American actress Fairuza Balk.
-
E.
Riza
Riza is a masculine given name commonly used in various cultures, often with roots in Arabic and Turkish languages.
- 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156866de48190a744e8dcaa0c66f1 |
completed | April 16, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5b0833081909668c042234b5b75 |
completed | May 9, 2026, 10:31 p.m. |
| NEDg | Description generation | batch_69ffb6a526188190be80658fb23cacbd |
completed | May 9, 2026, 10:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffb71cea948190a1c5998654aee8d5 |
completed | May 9, 2026, 10:37 p.m. |
Created at: April 10, 2026, 4:52 a.m.