Triple
T4945866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MUS |
E111047
|
entity |
| Predicate | labelFor |
P21560
|
FINISHED |
| Object | Museum station on transit maps |
—
|
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: Museum station on transit maps | Statement: [MUS, labelFor, Museum station on transit maps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: labelFor Context triple: [MUS, labelFor, Museum station on transit maps]
-
A.
labelOf
chosen
Indicates that one entity serves as the name, tag, or identifying label assigned to another entity.
-
B.
labelGroup
Indicates that an entity is assigned to or associated with a particular group label used for categorization or organization.
-
C.
hasLabel
Indicates that an entity is associated with a specific textual label or name used to identify or describe it.
-
D.
altLabel
Indicates an alternative name, label, or synonym used to refer to the same entity as the primary label.
-
E.
labelCatalog
Indicates assigning or associating a descriptive label or identifier with a catalog entity or catalog entry.
- 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_69bd441721cc819085c7e33fe0876818 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd70aa890c81908e685ec5e88cae1f |
completed | March 20, 2026, 4:07 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3aa1388190b3e0c8ee1ba1e4fa |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:31 p.m.