Triple
T2720889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth line |
E60076
|
entity |
| Predicate | readingShenfieldThroughRunningDate |
P41857
|
FINISHED |
| Object | 2023-05-21 |
—
|
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: 2023-05-21 | Statement: [Elizabeth line, readingShenfieldThroughRunningDate, 2023-05-21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: readingShenfieldThroughRunningDate Context triple: [Elizabeth line, readingShenfieldThroughRunningDate, 2023-05-21]
-
A.
containsReading
Indicates that one entity includes or encompasses a particular reading (such as a measurement, value, or interpretation) within it.
-
B.
readBy
Indicates that a particular text, document, or content item has been read or consumed by a specific person or agent.
-
C.
readingAid
Indicates that one entity assists or facilitates another entity’s ability to read or engage in reading activities.
-
D.
readsTo
Indicates that one entity reads or recites content aloud for the benefit of another entity.
-
E.
readingFeature
Indicates that an entity possesses a characteristic, capability, or attribute specifically related to reading.
- 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_69ab4b746d248190958e052045c09255 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdab1cb808190b0789c76bc9cb090 |
completed | March 7, 2026, 7:58 a.m. |
| PD | Predicate disambiguation | batch_69abd8240920819087a812d816a55edb |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd949c120819099a9d56eb71a0339 |
completed | March 7, 2026, 7:52 a.m. |
Created at: March 6, 2026, 9:55 p.m.