Triple
T3003731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christina Hendricks |
E81848
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Christina |
E75185
|
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: Christina | Statement: [Christina Hendricks, givenName, Christina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christina Context triple: [Christina Hendricks, givenName, Christina]
-
A.
Christina
chosen
Christina is a feminine given name widely used in many cultures, often associated with notable figures in entertainment, arts, and public life.
-
B.
Christina Bailey
Christina Bailey is a mysterious and doomed young woman whose frantic plea for help sets off the dark, twisting events of the classic 1955 film noir "Kiss Me Deadly."
-
C.
Christa
Christa was the first name of Christa McAuliffe, the American teacher and astronaut selected as the first private citizen to fly in space.
-
D.
Christina Navarro
Christina Navarro is a notable individual recognized for achievements significant enough to be distinctly associated with the surname Navarro.
-
E.
Cristina
Cristina is one of the two free-spirited American women at the center of Woody Allen’s romantic drama film "Vicky Cristina Barcelona."
- 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_69ad8b1c4de88190a83b7cefaa1f2842 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a149b248190ac4f11afc4871cc1 |
completed | March 8, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b12e5302c881908294827106b314e4 |
completed | March 11, 2026, 8:56 a.m. |
Created at: March 8, 2026, 2:59 p.m.