Triple
T7277778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | gluon |
E163072
|
entity |
| Predicate | hasNumberOfTypes |
P76192
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [gluon, hasNumberOfTypes, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfTypes Context triple: [gluon, hasNumberOfTypes, 8]
-
A.
hasObjectTypes
Indicates that something is associated with one or more specific categories or types of objects.
-
B.
originalNumberOfTypes
Indicates the initial total count of distinct types that existed before any changes, filtering, or transformations were applied.
-
C.
hasSignTypes
Indicates that an entity is associated with one or more specific types or categories of signs.
-
D.
hasApproximateNumberOfVarieties
Indicates that an entity is associated with an estimated or non-exact count of different varieties or types.
-
E.
hasMemberCountType
Indicates the type or classification used to describe how the number of members in a group or collection is represented.
- 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_69c6885c5964819085b209701769877f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb8a0b4881908ff27c5a75bd4a95 |
completed | March 27, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69c6e76a84a081908d4184c55b728e48 |
completed | March 27, 2026, 8:24 p.m. |
| PDg | Predicate description generation | batch_69c6eb88a2648190acc79eeee8733705 |
completed | March 27, 2026, 8:41 p.m. |
Created at: March 27, 2026, 2:59 p.m.