Triple
T3221035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snowy Hydro Scheme |
E67510
|
entity |
| Predicate | constructionWorkforce |
P3807
|
FINISHED |
| Object | more than 100000 workers over time |
—
|
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: more than 100000 workers over time | Statement: [Snowy Hydro Scheme, constructionWorkforce, more than 100000 workers over time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: constructionWorkforce Context triple: [Snowy Hydro Scheme, constructionWorkforce, more than 100000 workers over time]
-
A.
constructionLabor
Indicates a relationship where an entity performs or provides labor specifically for construction-related work or projects.
-
B.
employedPeople
Indicates that there exists a relationship where people are currently working in jobs or positions, typically under an employer.
-
C.
constructionSite
Indicates that an entity is a location or area where construction work is actively taking place or is planned to occur.
-
D.
involvesWorkers
chosen
Indicates that an event, process, or situation includes workers as active participants or affected parties.
-
E.
hasWorkforceType
Indicates the type or category of workforce associated with an entity (such as permanent, temporary, contract, or part-time).
- 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_69ad858b8adc8190ad989712c87a476b |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adae16f20081909d7f3bac016f961d |
completed | March 8, 2026, 5:12 p.m. |
| PD | Predicate disambiguation | batch_69ad9e0bb6c48190a0659c67d40ee37c |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:08 p.m.