Triple
T30644572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edison incandescent lamps |
E780085
|
entity |
| Predicate | hasFilamentType |
P196248
|
FINISHED |
| Object | carbon filament |
—
|
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: carbon filament | Statement: [Edison incandescent lamps, hasFilamentType, carbon filament]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFilamentType Context triple: [Edison incandescent lamps, hasFilamentType, carbon filament]
-
A.
hasMaterialType
Indicates that something is composed of, made from, or characterized by a specific type of material.
-
B.
hasFillingType
Indicates that an entity is associated with a specific type or category of filling it contains or uses.
-
C.
hasKilnType
Indicates a relationship where an entity is associated with or characterized by a specific type of kiln used in its production or processing.
-
D.
hasChipType
Indicates that an entity is associated with or uses a specific type or category of chip.
-
E.
hasNozzlesOn
Indicates that one object is equipped with or features nozzles positioned on another object or surface.
- 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_69f224a50ebc81909b961a94c7f66b12 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe189fec148190aeef51b417ba15b0 |
completed | May 8, 2026, 5:08 p.m. |
| PD | Predicate disambiguation | batch_69fe17285b0881908de7569d8dbd20bd |
completed | May 8, 2026, 5:02 p.m. |
| PDg | Predicate description generation | batch_69fe189f2ea48190b8c4718f1353970e |
completed | May 8, 2026, 5:08 p.m. |
Created at: April 29, 2026, 8:29 p.m.