Triple
T36684015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ballena (sculpture) |
E905766
|
entity |
| Predicate | hasDisplayCity |
P20677
|
FINISHED |
| Object | Mexico 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: Mexico City | Statement: [Ballena (sculpture), hasDisplayCity, Mexico City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDisplayCity Context triple: [Ballena (sculpture), hasDisplayCity, Mexico City]
-
A.
displayLocationCity
chosen
Indicates the city where something is shown, presented, or made visible.
-
B.
settingCity
Indicates that a work or event takes place in, or is primarily located within, a particular city.
-
C.
hasNearbyUSCity
Indicates that one location has at least one city in the United States situated within a specified nearby distance.
-
D.
hasCityQualifier
Indicates that a city is associated with an additional descriptive qualifier, such as a status, role, or distinguishing attribute.
-
E.
hasLocationCity
Indicates that an entity is situated in, occurs in, or is associated with a specific city as its location.
- 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_69f76e7011dc819082b324f18b756a1b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff6ef0d61c81909162d37c15a1a3c3 |
completed | May 9, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69ff6c6a58e08190921317062cd9d489 |
completed | May 9, 2026, 5:18 p.m. |
Created at: May 3, 2026, 4:12 p.m.