Triple
T268784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FABLife |
E5578
|
entity |
| Predicate | typicalSegmentType |
P9638
|
FINISHED |
| Object | style tips |
—
|
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: style tips | Statement: [FABLife, typicalSegmentType, style tips]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSegmentType Context triple: [FABLife, typicalSegmentType, style tips]
-
A.
typicalProductionType
Indicates the usual or characteristic type of production activity associated with an entity.
-
B.
trackType
Indicates the specific kind or category of track associated with an entity, such as its functional or physical classification.
-
C.
standardType
Indicates that one entity is classified as the standard, canonical, or reference type for another entity or context.
-
D.
typicalNotation
Indicates that one entity is the standard or commonly used symbolic representation (notation) for another entity.
-
E.
typicalKey
Indicates that the referenced key is the standard or most commonly used key associated with an 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_69a25853594c8190b05ec3a586ec88bf |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25dae4a0c8190a66cf6ed3889851c |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b70d99c819085d8381a313a2a34 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25d6ec9688190b2ba027756b57d25 |
completed | Feb. 28, 2026, 3:13 a.m. |
Created at: Feb. 28, 2026, 2:57 a.m.