Triple
T4391655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Newspaper and Current Periodical Reading Room |
E99376
|
entity |
| Predicate | hasReadingRoomType |
P56350
|
FINISHED |
| Object | specialized reading room |
—
|
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: specialized reading room | Statement: [Newspaper and Current Periodical Reading Room, hasReadingRoomType, specialized reading room]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReadingRoomType Context triple: [Newspaper and Current Periodical Reading Room, hasReadingRoomType, specialized reading room]
-
A.
hasReadingRoom
Indicates that a place or facility includes a designated reading room area available for use.
-
B.
hasReadingType
Indicates that an entity is associated with a specific category or mode of reading, such as a particular interpretation, format, or type of reading measurement.
-
C.
containsReading
Indicates that one entity includes or encompasses a particular reading (such as a measurement, value, or interpretation) within it.
-
D.
hasRoom
Indicates that an entity possesses, contains, or is associated with a specific room.
-
E.
hasReservationType
Indicates that an entity is associated with a specific category or type of reservation.
- 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_69b3454f739481909ff6c28331f0c0b9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35285592881909fcdea225a655950 |
completed | March 12, 2026, 11:55 p.m. |
| PD | Predicate disambiguation | batch_69b34f572efc8190bad1e5078cbcb75a |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b3501834448190bedf775a80da4778 |
completed | March 12, 2026, 11:45 p.m. |
Created at: March 12, 2026, 11:19 p.m.