Triple
T30362721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penny McCall |
E772331
|
entity |
| Predicate | wasInRelationshipDuring |
P169738
|
FINISHED |
| Object | 1970s |
—
|
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: 1970s | Statement: [Penny McCall, wasInRelationshipDuring, 1970s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasInRelationshipDuring Context triple: [Penny McCall, wasInRelationshipDuring, 1970s]
-
A.
hasBeenDatedBy
Indicates that one entity has previously been in a romantic or dating relationship with another entity.
-
B.
formerRelationshipStatus
Indicates that a relationship between entities existed in the past but no longer holds in the present.
-
C.
romanticRelationshipStatus
Indicates the nature or state of a romantic relationship between entities, such as whether they are dating, committed, separated, or otherwise romantically involved.
-
D.
relationshipDurationWith
Indicates the length of time that a specified relationship between two entities has existed or is expected to last.
-
E.
relationshipStatusDuringFilm
Indicates the type or state of a relationship between entities specifically during the time period in which a film takes place or is produced.
- 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_69f2248d71408190aec0d5c2001b1cff |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68243b5d8819092d8a0a1261f5fb2 |
completed | May 2, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f67f7e116c819099aec724e9ef3763 |
completed | May 2, 2026, 10:49 p.m. |
Created at: April 29, 2026, 7:58 p.m.