Triple
T23141124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Gallucci |
E577462
|
entity |
| Predicate | spouseOrderForMagdaGabor |
P4764
|
FINISHED |
| Object | third 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: third husband | Statement: [Tony Gallucci, spouseOrderForMagdaGabor, third husband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseOrderForMagdaGabor Context triple: [Tony Gallucci, spouseOrderForMagdaGabor, third husband]
-
A.
marriageOrderWithBelaLugosi
Indicates the chronological order in which an entity entered into marriage with Bela Lugosi.
-
B.
marriageOrderToBelaLugosi
Indicates the sequence or ranking of a person’s marriage in relation to their marriage to Bela Lugosi.
-
C.
spouseOrder
chosen
Indicates the position or sequence of a person among multiple spouses in a marital relationship.
-
D.
marriageOrderToClarkGable
Indicates the chronological position in which an entity married Clark Gable relative to his other spouses.
-
E.
marriageOrderRelativeToHattieMcDaniel
Indicates the position or sequence of a person’s marriage relative to Hattie McDaniel’s own marriages (e.g., before, after, or in comparison to a specific marriage of hers).
- F. None of above.
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_69e245f8e6248190ba3d58e068b4dccb |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18eca8a9081908dcc39409f615b7c |
completed | April 29, 2026, 4:53 a.m. |
| PD | Predicate disambiguation | batch_69ef89f83b108190aaaa1db6221fc163 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4 p.m.