Triple
T8465000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris O'Donnell |
E200137
|
entity |
| Predicate | characterPortrayed |
P1507
|
FINISHED |
| Object | Robin |
E308868
|
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: Robin | Statement: [Chris O'Donnell, characterPortrayed, Robin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robin Context triple: [Chris O'Donnell, characterPortrayed, Robin]
-
A.
Robin
Robin is a given name commonly used in various cultures, often as a diminutive or variant of names like Robert.
-
B.
Robin
chosen
Robin is the disciplined and strategic leader of the Teen Titans, a young superhero team in the DC Comics universe.
-
C.
Charlie
Charlie is the fictional Boston subway rider in the folk song "Charlie on the MTA," known for being unable to get off the train because he lacks the fare to exit.
-
D.
Charlie
Charlie is the young girl with powerful pyrokinetic abilities at the center of Stephen King’s novel "Firestarter."
-
E.
Charlie
Charlie is a central character in the romantic comedy film "French Kiss," serving as the unfaithful fiancé whose actions set the story’s events in motion.
- 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_69ca83198c4c8190a337bf717d1813f5 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe4d05b2881909bddf58df0ee1143 |
completed | March 31, 2026, 3:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce39e0d7788190add03271c940e1ff |
completed | April 2, 2026, 9:41 a.m. |
Created at: March 30, 2026, 6:11 p.m.