Triple
T4906301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LEED for Hospitality |
E109919
|
entity |
| Predicate | tailorsCreditsFor |
P59358
|
FINISHED |
| Object | guest rooms |
—
|
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: guest rooms | Statement: [LEED for Hospitality, tailorsCreditsFor, guest rooms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tailorsCreditsFor Context triple: [LEED for Hospitality, tailorsCreditsFor, guest rooms]
-
A.
creditedFor
Indicates that one entity is acknowledged as the source, contributor, or originator responsible for another entity (such as a work, achievement, or outcome).
-
B.
creditsAre
Indicates that certain credits are assigned, attributed, or owed to a particular entity or set of entities.
-
C.
hasNotableTailor
Indicates that an entity is associated with a tailor who is distinguished or noteworthy in some significant way.
-
D.
designedCostumesFor
Indicates that one entity created or planned the costumes used by another entity, typically for a performance, production, or event.
-
E.
grantsCreditFor
Indicates that one entity recognizes or awards academic or other formal credit to another entity for a specific activity, course, or achievement.
- 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_69bd441180708190ba42ffb44fea533a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e72ed5c819081104c99a398e0af |
completed | March 20, 2026, 3:57 p.m. |
| PD | Predicate disambiguation | batch_69bd6c325e188190823836d79934e9bc |
completed | March 20, 2026, 3:48 p.m. |
| PDg | Predicate description generation | batch_69bd6cc228088190849f23b7bd4cf549 |
completed | March 20, 2026, 3:50 p.m. |
Created at: March 20, 2026, 1:29 p.m.