Triple
T19812774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inn of Court |
E475986
|
entity |
| Predicate | numberOfConstituentBodies |
P5741
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Inn of Court, numberOfConstituentBodies, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfConstituentBodies Context triple: [Inn of Court, numberOfConstituentBodies, 4]
-
A.
numberOfConstituents
chosen
Indicates the total count of individual components or members that make up a larger whole or group.
-
B.
numberOfConstituentsType
Indicates the type or category used to classify how many constituents (parts or members) are involved in or associated with something.
-
C.
numberOfSolarSystemObjects
Indicates the quantitative count of solar system objects associated with or contained by a given entity.
-
D.
hasBodyPartCount
Indicates that an entity possesses a specified number of body parts.
-
E.
constitutedBy
Indicates that something is made up of, composed from, or formed by the specified parts or elements.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6542d7c048190818359cbf430f50e |
completed | April 20, 2026, 4:28 p.m. |
| PD | Predicate disambiguation | batch_69e5305858108190bbbfdb9ba3ab9f80 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:50 p.m.