Triple
T36864478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ray Singh |
E911032
|
entity |
| Predicate | firstKissWith |
P197180
|
FINISHED |
| Object | Susie Salmon |
E850919
|
NE 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: Susie Salmon | Statement: [Ray Singh, firstKissWith, Susie Salmon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstKissWith Context triple: [Ray Singh, firstKissWith, Susie Salmon]
-
A.
hasOnScreenKissWith
Indicates that two entities share a romantic or affectionate kiss depicted visually within the same on-screen scene.
-
B.
firstMeets
Indicates that one entity encounters or comes into contact with another entity for the first time.
-
C.
isChildhoodSweetheartOf
Indicates that two people were romantically involved with each other during their childhood or adolescence, typically as first or early sweethearts.
-
D.
hasRomanticEncounterWith
chosen
Indicates that two entities engage in or share a romantic or intimate encounter with each other.
-
E.
placeOfFirstCommunionOf
Indicates the location where an individual received their First Communion.
- F. None of above.
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_69f76e80f6f0819091cba8e19b269615 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3e1619e40c81908ff28290b59334f2 |
completed | June 26, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:13 p.m.