Triple
T30845693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parc de Marly |
E785624
|
entity |
| Predicate | waterSuppliedHistoricallyBy |
P90162
|
FINISHED |
| Object | Machine de Marly |
—
|
NE NERFINISHED |
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: Machine de Marly | Statement: [Parc de Marly, waterSuppliedHistoricallyBy, Machine de Marly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterSuppliedHistoricallyBy Context triple: [Parc de Marly, waterSuppliedHistoricallyBy, Machine de Marly]
-
A.
waterSourceHistoric
chosen
Indicates that one entity has historically served as a source or supply of water for the other.
-
B.
waterSupplyPopulationServed
Indicates the number of people that are provided with or served by a particular water supply system.
-
C.
waterSupplyShare
Indicates the proportion of a total water supply that is allocated to or used by a particular entity.
-
D.
waterUsedByCity
Indicates the amount of water consumed or utilized by a specific city.
-
E.
waterAllocatedTo
Indicates that a specified amount or portion of water has been designated or assigned for use by a particular entity, location, or purpose.
- 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_69f224b850848190a4af4ccf8ddadcdf |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fbc9d1dba881908c399b8e1dc13ce2 |
completed | May 6, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
Created at: April 29, 2026, 8:46 p.m.