Triple
T21751145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of Cluny |
E536914
|
entity |
| Predicate | numberOfHousesAtPeak |
P1264
|
FINISHED |
| Object | over 1,000 |
—
|
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: over 1,000 | Statement: [Order of Cluny, numberOfHousesAtPeak, over 1,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfHousesAtPeak Context triple: [Order of Cluny, numberOfHousesAtPeak, over 1,000]
-
A.
numberOfLocationsAtPeak
Indicates the total count of distinct locations associated with an entity at its highest or peak point in time or activity.
-
B.
numberOfHouses
chosen
Indicates the quantity of houses associated with a given entity or context.
-
C.
numberOfDistrictsPeak
Indicates the maximum number of districts that an entity reaches or has at its highest point over a given period or context.
-
D.
numberOfEmployeesAtPeak
Indicates the highest recorded count of employees that an entity had at any point in time.
-
E.
deploymentPeakNumber
Indicates the maximum number of deployments (or deployment instances) reached during a specified period or under given conditions.
- 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_69e0c46eab808190b848242d63a17c47 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01d8a6d4881908cc69e7247cce3a5 |
completed | April 28, 2026, 2:38 a.m. |
| PD | Predicate disambiguation | batch_69e6969c16fc8190b5126c169317d85d |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:50 p.m.