Triple
T4254261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Valentine |
E95932
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Valentine |
E113659
|
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: Valentine | Statement: [Don Valentine, familyName, Valentine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valentine Context triple: [Don Valentine, familyName, Valentine]
-
A.
Valentine
chosen
Valentine is a masculine given name of Latin origin commonly associated with the meaning "strong" or "healthy" and historically linked to Saint Valentine.
-
B.
The Valentine
The Valentine is a history museum in Richmond, Virginia, dedicated to preserving and interpreting the city’s past through exhibitions, collections, and educational programs.
-
C.
Valerie
"Valerie" is a 1957 American Western film starring Sterling Hayden, loosely inspired by the Rashomon-style multiple-perspective narrative.
-
D.
Valerie
Valerie is a sharp-tongued, quick-witted character in "The Princess Bride," known for helping her husband Miracle Max revive the hero Westley.
-
E.
Darling
Darling is the kind, affectionate human owner of Lady in Disney's animated film "Lady and the Tramp."
- 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_69b3453f759881909b91f01a1e82c036 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34ebe6fbc8190a89269b478b3f435 |
completed | March 12, 2026, 11:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5a887703c81909a40f23f83154b8c |
completed | March 14, 2026, 6:27 p.m. |
Created at: March 12, 2026, 11:06 p.m.