Triple
T27285667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tracy Tatro |
E688463
|
entity |
| Predicate | hasFeelingFor |
P140327
|
FINISHED |
| Object | Christopher McCandless |
—
|
NE NERFINISHED |
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: Christopher McCandless | Statement: [Tracy Tatro, hasFeelingFor, Christopher McCandless]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFeelingFor Context triple: [Tracy Tatro, hasFeelingFor, Christopher McCandless]
-
A.
romanticFeeling
chosen
Indicates that one entity experiences romantic attraction or affection toward another entity.
-
B.
loveInterest
Indicates that one entity is the romantic object of affection or attraction for another entity.
-
C.
loveInterestPortrayedBy
Indicates that a character’s romantic interest is depicted or played by a particular actor or performer.
-
D.
loveInterestType
Indicates the specific kind or category of romantic or affectionate relationship that exists between the related entities.
-
E.
hasPassion
Indicates that one entity feels a strong enthusiasm, interest, or love for another entity, activity, or subject.
- 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_69ef355998e08190bdff849e8f33adce |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 27, 2026, 11:11 a.m.