Triple
T4775041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal C (DFW) |
E106023
|
entity |
| Predicate | hasGatesFor |
P58717
|
FINISHED |
| Object | commercial airlines |
—
|
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: commercial airlines | Statement: [Terminal C (DFW), hasGatesFor, commercial airlines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGatesFor Context triple: [Terminal C (DFW), hasGatesFor, commercial airlines]
-
A.
hasGate
Indicates that one entity possesses, includes, or is equipped with a gate as part of its structure or configuration.
-
B.
hasGateRange
Indicates the range of values or interval within which a gate or gating parameter is valid or operates.
-
C.
hasFaregates
Indicates that an entity is equipped with or contains faregates used to control or validate access, typically for paid entry.
-
D.
hasCityGateStatus
Indicates the status or condition of a city gate in relation to a given entity.
-
E.
hasHistoricGate
Indicates that an entity possesses or is associated with a historically significant gate or gateway structure.
- 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_69bd43f3074c8190937e7b0a457fe9f1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6584481081908f1041a8827e0b42 |
completed | March 20, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69bd6229d8448190a271719e5e30fd82 |
completed | March 20, 2026, 3:05 p.m. |
| PDg | Predicate description generation | batch_69bd6508e218819086a36236cfa4a249 |
completed | March 20, 2026, 3:17 p.m. |
Created at: March 20, 2026, 1:21 p.m.