Triple
T33310290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shirley Valentine |
E852856
|
entity |
| Predicate | hasMainCharacterHometown |
P22139
|
FINISHED |
| Object | Liverpool |
—
|
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: Liverpool | Statement: [Shirley Valentine, hasMainCharacterHometown, Liverpool]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainCharacterHometown Context triple: [Shirley Valentine, hasMainCharacterHometown, Liverpool]
-
A.
homeTownInSeries
Indicates that a character’s hometown is located within a particular fictional series or narrative universe.
-
B.
hasHometownOf
chosen
Indicates that one entity has, as its hometown, the place represented by the other entity.
-
C.
homeTownInUniverse
Indicates that a location is the character’s hometown within a specified fictional or defined universe.
-
D.
hasMainPlace
Indicates that one entity is designated as the primary or central location associated with another entity.
-
E.
hasHomeCity
Indicates that an entity’s primary or official city of residence or affiliation is a specified city.
- 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_69f349679fd8819093b9b40e989440e3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a00d508290081909f3d5dfbb2e80c8e |
completed | May 10, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_6a00d49da4cc81909566ad286ec22292 |
completed | May 10, 2026, 6:55 p.m. |
Created at: May 1, 2026, 1:33 a.m.