Triple
T5948796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christine Hearst Schwarzman |
E132344
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Christine |
E181083
|
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: [Christine Hearst Schwarzman, hasGivenName, Christine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christine Context triple: [Christine Hearst Schwarzman, hasGivenName, Christine]
-
A.
Christine
chosen
Christine is a feminine given name of Greek origin meaning "follower of Christ," widely used in many Western countries.
-
B.
Christine
"Christine" is a 1980 post-punk/gothic rock single by Siouxsie and the Banshees, noted for its dark, atmospheric sound and psychologically themed lyrics.
-
C.
Christine
Christine is a horror novel by Stephen King about a possessed 1958 Plymouth Fury that exerts a deadly influence over its owner.
-
D.
Christine
Christine is a rival character to Heed, likely portrayed as a competitive or antagonistic counterpart in their shared narrative.
-
E.
Christine
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_69c00869d3308190af89b2453e0f7546 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0397deea08190b9397d0413740300 |
completed | March 22, 2026, 6:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c08d4f0481908547609bc2736380 |
completed | March 23, 2026, 4:24 a.m. |
Created at: March 22, 2026, 4:01 p.m.