Triple
T32690353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trane Technologies plc |
E835839
|
entity |
| Predicate | hasEmployeeCountApprox |
P17907
|
FINISHED |
| Object | ~40,000 |
—
|
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: ~40,000 | Statement: [Trane Technologies plc, hasEmployeeCountApprox, ~40,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmployeeCountApprox Context triple: [Trane Technologies plc, hasEmployeeCountApprox, ~40,000]
-
A.
employsApproximateNumberOfPeople
chosen
Indicates that an entity employs a roughly estimated or approximate number of people, rather than an exact headcount.
-
B.
hasApproximateNumberOfPeople
Indicates that an entity is associated with an estimated or approximate count of people, rather than an exact number.
-
C.
hasEmployees
Indicates that one entity employs one or more other entities as its workers or staff.
-
D.
employedApproximately
Indicates that one entity employs another in a manner where the number, duration, or extent of employment is approximate rather than exact.
-
E.
hasPopulationApproximate
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
- 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_69f3493211388190993801216afbc2a7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6cd126fcc8190aa1f1f146e45ec0c |
completed | May 3, 2026, 4:20 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1470808190b70cdfd7a6395670 |
completed | May 3, 2026, 4:16 a.m. |
Created at: May 1, 2026, 1:09 a.m.