Triple
T12471147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All England Lawn Tennis and Croquet Club |
E298057
|
entity |
| Predicate | courtCount |
P4502
|
FINISHED |
| Object | multiple grass match courts and practice courts |
—
|
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: multiple grass match courts and practice courts | Statement: [All England Lawn Tennis and Croquet Club, courtCount, multiple grass match courts and practice courts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courtCount Context triple: [All England Lawn Tennis and Croquet Club, courtCount, multiple grass match courts and practice courts]
-
A.
courtNumber
Indicates the specific numbered court (e.g., field, room, or venue) assigned or associated with an event, case, or match.
-
B.
numberOfCourts
chosen
Indicates the quantity of courts associated with or present at a given entity or location.
-
C.
courtCode
Indicates the specific court or judicial body associated with a legal case, proceeding, or record.
-
D.
courtConnection
Indicates a relationship where one entity is linked to another through a legal or judicial proceeding, institution, or decision.
-
E.
defendantCount
Indicates the number of defendants involved in a particular legal case or proceeding.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e626dbc8190ac7dcdb542ba9b0c |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d3f701c81909dd0e00251ac8553 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.