Triple
T3554453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christina |
E75185
|
entity |
| Predicate | hasVariant |
P455
|
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: [Christina, hasVariant, Christine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christine Context triple: [Christina, hasVariant, Christine]
-
A.
Christine
Christine is the birth name of Chrissy Teigen, an American model, television personality, and cookbook author.
-
B.
Christine
Christine is the protagonist of H. P. Lovecraft’s novel "Love," around whom the story’s emotional and psychological developments revolve.
-
C.
Christine
Christine is a character from the Marvel Cinematic Universe film "Iron Man 3," where she appears as the clairvoyant antagonist manipulating events from behind the scenes.
-
D.
Christine
chosen
Christine is a feminine given name of Greek origin meaning "follower of Christ," widely used in many Western countries.
-
E.
Christine
Christine is the given name of Canadian soccer legend Christine Sinclair, one of the most prolific goal scorers in international football history.
- 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_69ad85d33c6c819081d5ac1df13b5680 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc05549d88190acdebdd542ea1a67 |
completed | March 8, 2026, 6:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38bf1c3e881908e7fc3b4df24e72b |
completed | March 13, 2026, 4 a.m. |
Created at: March 8, 2026, 3:20 p.m.