Triple
T23895432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evelyn Harper |
E600889
|
entity |
| Predicate | hasRomanticHistory |
P97763
|
FINISHED |
| Object | multiple husbands |
—
|
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: multiple husbands | Statement: [Evelyn Harper, hasRomanticHistory, multiple husbands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRomanticHistory Context triple: [Evelyn Harper, hasRomanticHistory, multiple husbands]
-
A.
hasRomanticMisadventures
Indicates that an entity experiences a series of problematic, comical, or unsuccessful romantic relationships or encounters.
-
B.
hadPartner
chosen
Indicates that an entity was in a romantic or life-partner relationship with another entity at some point in time.
-
C.
hasRomanticSubplot
Indicates that a work includes a secondary storyline centered on a romantic relationship between characters.
-
D.
hasBeenDatedBy
Indicates that one entity has previously been in a romantic or dating relationship with another entity.
-
E.
hasAffairWith
Indicates that one entity is engaged in a secret or illicit romantic or sexual relationship with another entity, typically outside a committed partnership.
- 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_69e295341ac0819080647f2908af793c |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cdd9203081909b10820a81c5d9d3 |
completed | April 29, 2026, 9:22 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:25 p.m.