Triple
T3802109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LW2 |
E91711
|
entity |
| Predicate | featureLevel |
P20332
|
FINISHED |
| Object | intermediate equipment package |
—
|
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: intermediate equipment package | Statement: [LW2, featureLevel, intermediate equipment package]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featureLevel Context triple: [LW2, featureLevel, intermediate equipment package]
-
A.
featureLevelComparedTo
Indicates a comparative relationship between entities based on their feature level, specifying how one entity’s feature level ranks relative to another’s.
-
B.
level2Feature
chosen
Indicates that an entity possesses or is associated with a secondary or intermediate-level feature within a hierarchical feature structure.
-
C.
level1Feature
Indicates that one entity possesses or is associated with a primary or first-tier feature of another entity.
-
D.
featureType
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
E.
featureSet
Indicates that one entity is a collection or configuration of features associated with or applied to another entity.
- F. None of above.
Provenance (3 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_69aed96354f48190a768966d6bd19b04 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee8db8a288190afd1e3b9dcf02e97 |
completed | March 9, 2026, 3:35 p.m. |
| PD | Predicate disambiguation | batch_69aee7461abc8190945716f4b93e1a18 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:15 p.m.