Triple
T19340684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tremont House (Boston hotel) |
E483745
|
entity |
| Predicate | hasNumberOfWaterClosets |
P16001
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Tremont House (Boston hotel), hasNumberOfWaterClosets, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfWaterClosets Context triple: [Tremont House (Boston hotel), hasNumberOfWaterClosets, 12]
-
A.
hasRestrooms
Indicates that a place or facility provides access to restroom or toilet amenities.
-
B.
numberOfBathrooms
chosen
Indicates the total count of bathrooms associated with an entity (such as a property or unit).
-
C.
hasCleaningFacility
Indicates that an entity provides or is equipped with a facility or service for cleaning.
-
D.
hasAblutionFacilities
Indicates that an entity provides or is equipped with facilities for performing ablution or ritual washing.
-
E.
hasNumberOfPublicBathhouses
Indicates the quantity of public bathhouses associated with 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_69d8e8d244f8819080eb1f3491300db2 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e61856c0948190a3166b3bf3810e43 |
completed | April 20, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69e4dd12303c8190a2027c062b2dff40 |
completed | April 19, 2026, 1:48 p.m. |
Created at: April 10, 2026, 1:33 p.m.