Triple
T29498414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stanley Reames |
E748301
|
entity |
| Predicate | spouseOrderRelativeToJanetLeigh |
P184856
|
FINISHED |
| Object | first husband |
—
|
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: first husband | Statement: [Stanley Reames, spouseOrderRelativeToJanetLeigh, first husband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseOrderRelativeToJanetLeigh Context triple: [Stanley Reames, spouseOrderRelativeToJanetLeigh, first husband]
-
A.
spouseOrder
Indicates the position or sequence of a person among multiple spouses in a marital relationship.
-
B.
marriageOrderRelativeToJasonRobards
Indicates the position or sequence of a marriage in relation to Jason Robards’ own marriages (e.g., earlier, later, or specific ordinal order).
-
C.
motherSpouseOrder
Indicates that the subject is the spouse of the object’s mother, with an ordering or ranking among multiple such spouses.
-
D.
spouseOrderRelativeToGeneRoddenberry
Indicates the position or sequence of a person among Gene Roddenberry’s spouses (e.g., first spouse, second spouse, etc.).
-
E.
marriageOrderToLanaTurner
Indicates the ordinal position in which someone married Lana Turner among her 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_69f0bd448c6881908aa6b475cefd5ddc |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f7b628b17c8190aa058c1a51852a27 |
completed | May 3, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c06f5881908f0b98cad6796478 |
completed | May 3, 2026, 8:49 p.m. |
| PDg | Predicate description generation | batch_69f7b5cadd308190a864245a21b08f9a |
completed | May 3, 2026, 8:53 p.m. |
Created at: April 28, 2026, 4:21 p.m.