Triple
T27863644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barry Comden |
E704294
|
entity |
| Predicate | marriageOrderWithDorisDay |
P173367
|
FINISHED |
| Object | third husband of Doris Day |
—
|
LITERAL 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: third husband of Doris Day | Statement: [Barry Comden, marriageOrderWithDorisDay, third husband of Doris Day]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageOrderWithDorisDay Context triple: [Barry Comden, marriageOrderWithDorisDay, third husband of Doris Day]
-
A.
marriageOrderWithBillyBobThornton
Indicates the chronological position in which an entity was married to Billy Bob Thornton relative to his other spouses.
-
B.
marriageOrderWithMayaAngelou
Indicates the ordinal position in which an entity married Maya Angelou relative to her other spouses.
-
C.
marriageOrderRelativeToOrsonWelles
Indicates the position or sequence of a person’s marriage relative to Orson Welles’s own marriages (e.g., earlier, later, or same order).
-
D.
marriageOrderWithBelaLugosi
Indicates the chronological order in which an entity entered into marriage with Bela Lugosi.
-
E.
marriageOrderWithTonyBennett
Indicates the ordinal position in which an entity married Tony Bennett relative to his other spouses.
- F. None of above. chosen
Provenance (4 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_69ef840f12408190b539d00d79658abf |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f6b56ed31481908c3e5d749e46bad9 |
completed | May 3, 2026, 2:39 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a5fd8481909433e923c5e24e55 |
completed | May 3, 2026, 2:32 a.m. |
| PDg | Predicate description generation | batch_69f6b49339048190b617a6749f648825 |
completed | May 3, 2026, 2:36 a.m. |
Created at: April 27, 2026, 6:19 p.m.