Triple
T24872992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danny Martin |
E622485
|
entity |
| Predicate | relationshipBeginsAs |
P146883
|
FINISHED |
| Object | one-night stand |
—
|
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: one-night stand | Statement: [Danny Martin, relationshipBeginsAs, one-night stand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipBeginsAs Context triple: [Danny Martin, relationshipBeginsAs, one-night stand]
-
A.
relationshipDevelopsWith
Indicates that a relationship grows, evolves, or becomes more developed between two entities over time.
-
B.
relationshipTypeStart
chosen
Indicates the type or category of relationship that begins or is initiated at a specific point or event.
-
C.
relationshipStartEvent
Indicates the event or point in time at which a particular relationship between entities begins.
-
D.
relationshipDurationWith
Indicates the length of time that a specified relationship between two entities has existed or is expected to last.
-
E.
relationshipStartYear
Indicates the calendar year in which a particular relationship between entities was initiated.
- 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_69e2fac3fdbc81909c2ec49be5743cd9 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f650c70d7c819093d9a0f005f7c8d5 |
completed | May 2, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69f64cab1f648190a2a9460690d18a37 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 18, 2026, 5:23 a.m.