Triple
T6617884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | hammer, hoe and brush emblem |
E149598
|
entity |
| Predicate | hammerRepresents |
P71544
|
FINISHED |
| Object | industrial workers |
—
|
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: industrial workers | Statement: [hammer, hoe and brush emblem, hammerRepresents, industrial workers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hammerRepresents Context triple: [hammer, hoe and brush emblem, hammerRepresents, industrial workers]
-
A.
stoneUse
Indicates that one entity uses or employs stone as a material or tool for some purpose or activity.
-
B.
haka
Indicates a performance or execution of a haka, typically as a ceremonial or expressive action directed toward or in the presence of others.
-
C.
HamIs
Indicates that one entity is identified, classified, or equated as ham in relation to another entity.
-
D.
hornCount
Indicates the number of horns possessed by an entity.
-
E.
knifeName
Indicates that a particular name is assigned to or used for a given knife.
- 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_69c687ed8a9c81908bb671717cb192ef |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6bdb88cc881908f35648c15a7dc85 |
completed | March 27, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69c6ad007c1c8190af425f51011c7ad1 |
completed | March 27, 2026, 4:14 p.m. |
| PDg | Predicate description generation | batch_69c6bdb76ec48190b59d576170970cc9 |
completed | March 27, 2026, 5:26 p.m. |
Created at: March 27, 2026, 1:58 p.m.