Triple
T12425912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Megan Fox |
E296897
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Megan |
E158530
|
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: Megan | Statement: [Megan Fox, givenName, Megan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Megan Context triple: [Megan Fox, givenName, Megan]
-
A.
Megan
chosen
Megan is the full first name of Meg Griffin, the often-mocked teenage daughter character from the animated television series "Family Guy."
-
B.
Megan
Megan is a person romantically involved with Axel Palmer.
-
C.
Megan Morgan
Megan Morgan is a character from the 1988 sci-fi horror comedy film "Critters 2: The Main Course."
-
D.
Megan Hunt
Megan Hunt is the brilliant but emotionally complex medical examiner protagonist of the television series "Body of Proof."
-
E.
Megan Wollover
Megan Wollover is an American model and producer best known for her marriage to comedian and actor Tracy Morgan.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d7ccda08190be2ff1739c1c6855 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63499061881908d25af7c3474f774 |
completed | May 2, 2026, 5:30 p.m. |
Created at: April 8, 2026, 9:55 p.m.