Triple
T15888319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trentham Monkey Forest |
E385246
|
entity |
| Predicate | hasApproximateNumberOfMonkeys |
P120939
|
FINISHED |
| Object | 140 |
—
|
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: 140 | Statement: [Trentham Monkey Forest, hasApproximateNumberOfMonkeys, 140]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfMonkeys Context triple: [Trentham Monkey Forest, hasApproximateNumberOfMonkeys, 140]
-
A.
numberOfMonksApprox
Indicates an approximate count or estimate of how many monks are involved or present in a given context.
-
B.
hasNumberOfMonoliths
Indicates the specific count of monoliths associated with a given entity.
-
C.
hasPrimate
Indicates that one entity possesses, contains, or is associated with a primate.
-
D.
approximateNumberOfMoai
Indicates that one entity specifies an estimated or approximate count of Moai associated with another entity.
-
E.
hasCurrentPrimate
Indicates that an entity currently has a specific primate associated with it, such as in a role, position, or status.
- F. None of above. chosen
Provenance (4 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142c3e18c8190bb7b023f4a0eaebb |
completed | April 16, 2026, 8:12 p.m. |
| PDg | Predicate description generation | batch_69e174da2c2c819099ec46616798245a |
completed | April 16, 2026, 11:46 p.m. |
Created at: April 10, 2026, 4:51 a.m.