Triple
T12414723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waldorf Astoria Washington DC |
E296605
|
entity |
| Predicate | renovationForHotelUse |
P11548
|
FINISHED |
| Object | 2013–2016 |
—
|
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: 2013–2016 | Statement: [Waldorf Astoria Washington DC, renovationForHotelUse, 2013–2016]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: renovationForHotelUse Context triple: [Waldorf Astoria Washington DC, renovationForHotelUse, 2013–2016]
-
A.
renovationPurpose
chosen
Indicates that an entity is being renovated with a specific intended goal, use, or outcome in mind.
-
B.
renovationFeature
Indicates that an entity has a specific renovation-related characteristic, element, or improvement associated with it.
-
C.
requiresRenovation
Indicates that an entity is in a condition that necessitates repair, updating, or refurbishment before it is suitable for normal use or standards.
-
D.
hasRenovation
Indicates that an entity has undergone, is undergoing, or is associated with a renovation process or renovation event.
-
E.
capacityAfterRenovation
Indicates the number of occupants or units a place can hold once renovation work has been completed.
- 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_69d6ad9f464c81909db36d7e96e34b9e |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e1888b48190bd750f839a26e99e |
completed | April 10, 2026, 7:23 p.m. |
| PD | Predicate disambiguation | batch_69d94d354b488190adc83fb4f2770dd5 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:55 p.m.