Triple
T4080480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Very Large Array |
E87465
|
entity |
| Predicate | numberOfConfigurations |
P52889
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Very Large Array, numberOfConfigurations, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfConfigurations Context triple: [Very Large Array, numberOfConfigurations, 4]
-
A.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
B.
numberOfInstances
Indicates the quantity or count of distinct occurrences or instances associated with a given entity or context.
-
C.
numberOfPositions
Indicates the total count of distinct positions or roles associated with a given entity.
-
D.
variantCount
Indicates the number of distinct variants associated with a given entity or item.
-
E.
numberOfMECs
Indicates the quantity or count of MECs associated with a given entity or context.
- 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_69aed9435cf48190ad1da737c962d19d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc5204d881909829de15015aa50d |
completed | March 9, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69aef9082c2081908474f082a49bebc8 |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aef9b34dec81909bbc3def9decc71a |
completed | March 9, 2026, 4:47 p.m. |
Created at: March 9, 2026, 3:39 p.m.