Triple
T10769825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upangas |
E254044
|
entity |
| Predicate | numberOfTexts |
P95874
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Upangas, numberOfTexts, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTexts Context triple: [Upangas, numberOfTexts, 12]
-
A.
numberOfMainTexts
Indicates the quantity of primary or main textual components associated with an entity.
-
B.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
C.
numberOfDialogues
Indicates the total count of dialogues associated with or occurring between the referenced entities.
-
D.
numberOfCharacters
Indicates the total count of individual characters present in a given text, string, or entity’s representation.
-
E.
wordCount
Indicates the total number of words contained in a given text or linguistic unit.
- 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d732307fb88190ba1447f68523c58a |
completed | April 9, 2026, 4:59 a.m. |
| PD | Predicate disambiguation | batch_69d6f31455648190b5c24690487b1b54 |
completed | April 9, 2026, 12:30 a.m. |
| PDg | Predicate description generation | batch_69d6fa323564819097b207eb53f8a9b8 |
completed | April 9, 2026, 1 a.m. |
Created at: April 8, 2026, 9:16 p.m.