Triple
T36747127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Longwood (historic house) |
E907796
|
entity |
| Predicate | numberOfRoomsCompleted |
P205030
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Longwood (historic house), numberOfRoomsCompleted, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRoomsCompleted Context triple: [Longwood (historic house), numberOfRoomsCompleted, 9]
-
A.
numberCompleted
Indicates the total count of instances in which the related task, process, or item has been fully completed.
-
B.
numberOfRulesCompleted
Indicates the count of rules that have been successfully completed or satisfied in a given context.
-
C.
lapsCompleted
Indicates that an entity has finished a specified number of laps in a repeated circuit or course.
-
D.
hasStateRooms
Indicates that an entity (such as a ship, building, or facility) contains or is equipped with state rooms.
-
E.
numberOfHotelRooms
Indicates the total count of rooms that a given hotel has.
- 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_69f76e76d10881909ec1679bc043108c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:12 p.m.