Triple
T13065127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chrissy Metz |
E329301
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Christine |
E5573
|
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: Christine | Statement: [Chrissy Metz, givenName, Christine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christine Context triple: [Chrissy Metz, givenName, Christine]
-
A.
Christine
Christine is the protagonist of H. P. Lovecraft’s novel "Love," around whom the story’s emotional and psychological developments revolve.
-
B.
Christine
Christine is a fictional character from the 1951 British drama film "Journey into Light."
-
C.
Christine
Christine is a rival character to Heed, likely portrayed as a competitive or antagonistic counterpart in their shared narrative.
-
D.
Christine
Christine is a central character in the 1973 mystery film "The Last of Sheila," around whom key elements of the movie’s intricate whodunit plot revolve.
-
E.
Christine
chosen
Christine is the birth name of Chrissy Teigen, an American model, television personality, and cookbook author.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980eb81948190b27eb9ae19978079 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbe630808190a9a3481127bbaa86 |
completed | May 3, 2026, 4:15 a.m. |
Created at: April 9, 2026, 8:59 p.m.