Triple
T15929985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort Worth Alliance Airport |
E386297
|
entity |
| Predicate | hasIndustrialTenants |
P3277
|
FINISHED |
| Object | logistics companies |
—
|
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: logistics companies | Statement: [Fort Worth Alliance Airport, hasIndustrialTenants, logistics companies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIndustrialTenants Context triple: [Fort Worth Alliance Airport, hasIndustrialTenants, logistics companies]
-
A.
hasTenants
chosen
Indicates that an entity occupies or rents space from another entity as its tenant.
-
B.
hasIndustrialAreaType
Indicates that an entity’s industrial area is classified as a specific type or category of industrial zone.
-
C.
hasIndustrialEmployer
Indicates that an entity is employed by, or has an employment relationship with, an industrial organization or company.
-
D.
hasIndustrialAndOfficeParks
Indicates that an entity possesses or contains designated areas used for industrial facilities and office complexes.
-
E.
hasIndustrialZoneAlong
Indicates that an industrial zone is located adjacent to or extending along the length of a specified linear feature (such as a road, river, or boundary).
- 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e172b48b308190bc430b2308cbc75b |
completed | April 16, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69e142cf5c548190a931f7b58144cd31 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:52 a.m.