Triple
T16458344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Litherland Library |
E399739
|
entity |
| Predicate | hasReadingArea |
P6669
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Litherland Library, hasReadingArea, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReadingArea Context triple: [Litherland Library, hasReadingArea, yes]
-
A.
hasReadingRoom
chosen
Indicates that a place or facility includes a designated reading room area available for use.
-
B.
containsReading
Indicates that one entity includes or encompasses a particular reading (such as a measurement, value, or interpretation) within it.
-
C.
hasReading
Indicates that an entity is associated with a particular reading, such as a measured value, interpretation, or recorded observation.
-
D.
hasReadingRoomType
Indicates that an entity (such as a facility or building) has a specific type or category of reading room.
-
E.
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.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32d7ef5cc819084cfeb1a3e39d3cc |
completed | April 18, 2026, 7:06 a.m. |
| PD | Predicate disambiguation | batch_69e227048d608190a4205eae3117629a |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:10 a.m.