Triple
T29343048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S-100 bus |
E744086
|
entity |
| Predicate | typicalCardFormFactor |
P9336
|
FINISHED |
| Object | plug-in board with 100-pin edge connector |
—
|
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: plug-in board with 100-pin edge connector | Statement: [S-100 bus, typicalCardFormFactor, plug-in board with 100-pin edge connector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCardFormFactor Context triple: [S-100 bus, typicalCardFormFactor, plug-in board with 100-pin edge connector]
-
A.
targetFormFactor
Indicates the specific physical configuration or design format that something is intended to be used with or fit into.
-
B.
hasFormFactor
chosen
Indicates that one entity possesses or is characterized by a particular physical or structural form factor defined by another entity.
-
C.
deviceShape
Indicates that one entity has the physical form or geometric configuration specified by the other entity.
-
D.
tabletForm
Indicates that something exists or is provided in tablet dosage form.
-
E.
hasFormFactorDetail
Indicates a relationship where specific physical or structural characteristics of an entity’s form factor are specified or detailed.
- 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_69f09126cfcc8190899b16fbf3c2bf7b |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_6a01a23d8b148190ac2c8765aa9227c4 |
completed | May 11, 2026, 9:32 a.m. |
| PD | Predicate disambiguation | batch_6a01a1e8bb90819096647e929bfb3db8 |
completed | May 11, 2026, 9:31 a.m. |
Created at: April 28, 2026, 1:34 p.m.