Triple
T11990574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacob Portman |
E285392
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Portman |
E247494
|
NE FINISHED |
How this triple was built (2 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: Portman | Statement: [Jacob Portman, familyName, Portman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Portman Context triple: [Jacob Portman, familyName, Portman]
-
A.
Portman
chosen
Portman is the surname of Natalie Portman, the acclaimed Israeli-American actress and filmmaker known for roles in films such as "Black Swan" and the "Star Wars" prequel trilogy.
-
B.
Reid
Reid is a common Scottish and Irish surname that has been borne by numerous notable figures across fields such as science, politics, and the arts.
-
C.
Peter Snowe
Peter Snowe was an American politician from Maine who served in the state legislature and was the first husband of U.S. Senator Olympia Snowe.
-
D.
Luke Adams
Luke Adams is an actor known for playing the character Kevin Swanson.
-
E.
Terance Mann
Terance Mann is a professional basketball player known for his versatile wing play in the NBA after starring in college at Florida State.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903afe4388190a2cf2328e85adf9b |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f47257911481909d6bd72535eefdbd |
completed | May 1, 2026, 9:28 a.m. |
Created at: April 8, 2026, 9:46 p.m.