Triple
T37888073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liberty Paints |
E945051
|
entity |
| Predicate | hasWorkLocationInFiction |
P91344
|
FINISHED |
| Object | New York City |
—
|
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: New York City | Statement: [Liberty Paints, hasWorkLocationInFiction, New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkLocationInFiction Context triple: [Liberty Paints, hasWorkLocationInFiction, New York City]
-
A.
hasBranchInFictionalLocation
chosen
Indicates that an organization maintains a branch, office, or presence within a fictional or imaginary location.
-
B.
basedInFictionalWorkLocation
Indicates that an entity’s location or setting is situated within a fictional place as depicted in a specific creative work.
-
C.
worksAtFictionalPlace
Indicates that an entity is employed at or associated with performing work in a fictional or imaginary location.
-
D.
hasPlaceInFiction
Indicates that a fictional work or element is associated with, set in, or takes place within a particular fictional location or setting.
-
E.
performedAtFictionalLocation
Indicates that an action or event took place at a location that exists only in a fictional or imagined context.
- 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_69f76ef02668819089e7940c4001af5e |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fef3ceef648190b58027c93d757438 |
completed | May 9, 2026, 8:43 a.m. |
| PD | Predicate disambiguation | batch_69fef359da2c819091a034387b08821f |
completed | May 9, 2026, 8:42 a.m. |
Created at: May 3, 2026, 4:19 p.m.