Triple
T10849105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TxTag |
E256092
|
entity |
| Predicate | readsBy |
P18381
|
FINISHED |
| Object | overhead gantry readers |
—
|
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: overhead gantry readers | Statement: [TxTag, readsBy, overhead gantry readers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: readsBy Context triple: [TxTag, readsBy, overhead gantry readers]
-
A.
readsTo
Indicates that one entity reads or recites content aloud for the benefit of another entity.
-
B.
readBy
chosen
Indicates that a particular text, document, or content item has been read or consumed by a specific person or agent.
-
C.
readsFrom
Indicates that one entity obtains or accesses data, information, or content from another entity as a source.
-
D.
containsReading
Indicates that one entity includes or encompasses a particular reading (such as a measurement, value, or interpretation) within it.
-
E.
reading
Indicates that an entity is engaged in the activity of interpreting and understanding written or printed material from another entity or source.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75115e4a88190b77be46b63db0c84 |
completed | April 9, 2026, 7:11 a.m. |
| PD | Predicate disambiguation | batch_69d70d2b51448190bae748ed6c23edde |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:20 p.m.