Triple
T11266269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lane’s End Farm |
E266693
|
entity |
| Predicate | hasStallionRosterSize |
P15427
|
FINISHED |
| Object | one of the largest in Kentucky |
—
|
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: one of the largest in Kentucky | Statement: [Lane’s End Farm, hasStallionRosterSize, one of the largest in Kentucky]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStallionRosterSize Context triple: [Lane’s End Farm, hasStallionRosterSize, one of the largest in Kentucky]
-
A.
hasHerdSize
Indicates the number of individual animals that belong to a particular herd.
-
B.
rosterSize
chosen
Indicates the total number of individuals included on a given roster.
-
C.
notableStallionStood
Indicates that a notable stallion was stationed, kept, or used for breeding at a particular location or stud.
-
D.
numberOfStoneHorses
Indicates the quantity of stone horses associated with a given subject or location.
-
E.
hasNumberOfDefencemen
Indicates the relationship that specifies how many defencemen are associated with or assigned to a given entity.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e94e5e3c8190a31995d55d20d7ed |
completed | April 9, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69d7879bc56c8190b2e8d2193f29de05 |
completed | April 9, 2026, 11:03 a.m. |
Created at: April 8, 2026, 9:31 p.m.