Triple
T9117925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zócalo metro station |
E218769
|
entity |
| Predicate | hasStationIcon |
P87191
|
FINISHED |
| Object | silhouette of the Metropolitan Cathedral |
—
|
LITERAL 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: silhouette of the Metropolitan Cathedral | Statement: [Zócalo metro station, hasStationIcon, silhouette of the Metropolitan Cathedral]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStationIcon Context triple: [Zócalo metro station, hasStationIcon, silhouette of the Metropolitan Cathedral]
-
A.
hasStationFunction
Indicates that an entity serves in a particular functional role or capacity at a station.
-
B.
hasStations
Indicates that one entity possesses, contains, or is associated with one or more stations.
-
C.
hasStationCode
Indicates that an entity is associated with a specific station identification code.
-
D.
hasStationStructure
Indicates that an entity possesses or is associated with a particular station-related physical structure.
-
E.
hasStationInCity
Indicates that a station or facility is located within a particular city.
- F. None of above. chosen
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_69ca83dc94ac8190b9ef42684d36ff39 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8a5e2ac8190b602ef0c77deb2fa |
completed | April 1, 2026, 5:09 a.m. |
| PD | Predicate disambiguation | batch_69cc66003e3c819091e1e42c9cf7c781 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc6a3c78388190a7436acc0e44ff55 |
completed | April 1, 2026, 12:43 a.m. |
Created at: March 30, 2026, 7:17 p.m.