Triple
T23730339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Chinaski |
E586392
|
entity |
| Predicate | hasLoveInterests |
P98395
|
FINISHED |
| Object | multiple women |
—
|
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 women | Statement: [Henry Chinaski, hasLoveInterests, multiple women]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLoveInterests Context triple: [Henry Chinaski, hasLoveInterests, multiple women]
-
A.
loveInterestPortrayedBy
Indicates that a character’s romantic interest is depicted or played by a particular actor or performer.
-
B.
hasRomanticTensionWith
Indicates a mutual or one-sided romantic attraction or unresolved romantic interest existing between two entities.
-
C.
hasLoveInterestInWork
Indicates that one entity is portrayed as a romantic love interest of another entity within a specific creative work.
-
D.
hasLoveLifeCharacteristic
chosen
Indicates that an entity possesses a particular quality, status, or attribute related to its romantic or love life.
-
E.
rumoredLoverOf
Indicates that one entity is widely believed or speculated to be the romantic partner or lover of another entity, without confirmed evidence.
- 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_69e24907dc9c8190be074c9c96a0ec2d |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b9180bf48190a6c3656ef0530463 |
completed | April 29, 2026, 7:54 a.m. |
| PD | Predicate disambiguation | batch_69f155e4b1148190836ede4741dcb888 |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 7:09 p.m.