Triple
T527215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Tax Court |
E10945
|
entity |
| Predicate | travelsOn |
P15183
|
FINISHED |
| Object | national trial calendar |
—
|
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: national trial calendar | Statement: [United States Tax Court, travelsOn, national trial calendar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelsOn Context triple: [United States Tax Court, travelsOn, national trial calendar]
-
A.
involvedTravelBetween
Indicates a relationship where an entity participates in or is associated with travel occurring between two specified locations.
-
B.
transports
Indicates that one entity carries or conveys another entity from one place to another.
-
C.
landedOnBy
Indicates that one entity has come down to rest upon or make contact with the surface of another entity.
-
D.
hasTransportRoute
Indicates that there exists a designated transportation connection or route linking one entity to another.
-
E.
hasGroundTransportation
Indicates that an entity provides, includes, or is connected to transportation services or options that operate on land (e.g., cars, buses, trains).
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1d2851c81908129f7da932ab7b3 |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f0198ecc8190883849e5a8245963 |
completed | Feb. 28, 2026, 1:39 p.m. |
| PDg | Predicate description generation | batch_69a2f0dcff1881909c18e8c599c150a1 |
completed | Feb. 28, 2026, 1:42 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.