Triple
T9592006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T-AGOR-28 |
E231442
|
entity |
| Predicate | numberWithinClass |
P89977
|
FINISHED |
| Object | 28 |
—
|
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: 28 | Statement: [T-AGOR-28, numberWithinClass, 28]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberWithinClass Context triple: [T-AGOR-28, numberWithinClass, 28]
-
A.
numberInClass
Indicates that a specified entity is a member of, or belongs to, a particular class or category.
-
B.
numberWithinSite
Indicates that an entity has a specific identifying number or position assigned within the context of a particular site or location.
-
C.
lengthClass
Indicates a classification relationship where an entity is assigned to a category based on its length.
-
D.
currentNumberOfClasses
Indicates the present count of classes associated with or contained by a given entity.
-
E.
hasNumberWithinWork
Indicates that a specific number or numeric value is contained, referenced, or used within a particular work (such as a document, publication, or creative piece).
- 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_69ca8482884481908eccdfdf64d6fbf7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9a10b85881908bfc783dcb7170aa |
completed | April 1, 2026, 10:20 p.m. |
| PD | Predicate disambiguation | batch_69ccd5a359788190b24f82399489f7fe |
completed | April 1, 2026, 8:21 a.m. |
| PDg | Predicate description generation | batch_69ccd93e90048190a2b0d7c5c195ba98 |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:06 p.m.