Triple
T37494258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexico City Metro Line 12 |
E931783
|
entity |
| Predicate | hasTrackCharacter |
P115884
|
FINISHED |
| Object | underground |
—
|
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: underground | Statement: [Mexico City Metro Line 12, hasTrackCharacter, underground]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrackCharacter Context triple: [Mexico City Metro Line 12, hasTrackCharacter, underground]
-
A.
hasTrack
Indicates that one entity possesses, includes, or is associated with a specific track (such as a path, course, or recorded item).
-
B.
hasTrackWith
Indicates that something includes, contains, or is associated with a specific track (such as a path, course, or recorded item).
-
C.
hasTrackControl
Indicates that one entity has authority or capability to manage, direct, or regulate the operation or behavior of another entity’s track or tracking process.
-
D.
hasTrackFeatures
chosen
Indicates that something possesses or is associated with specific track-related characteristics or attributes.
-
E.
hasTrackSection
Indicates that an entity includes, is composed of, or is associated with a specific section or segment of a track.
- 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_69f76ec457a4819094eeb3aed9baac11 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a0039c2d5d48190b8ef2c7ef17d8dc5 |
completed | May 10, 2026, 7:54 a.m. |
| PD | Predicate disambiguation | batch_6a0038e525448190a4c815f51595e78d |
completed | May 10, 2026, 7:51 a.m. |
Created at: May 3, 2026, 4:17 p.m.