Triple
T17778171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferrería/Arena Ciudad de México |
E443826
|
entity |
| Predicate | hasSymbolDescription |
P15163
|
FINISHED |
| Object | silhouette of a cow’s head |
—
|
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: silhouette of a cow’s head | Statement: [Ferrería/Arena Ciudad de México, hasSymbolDescription, silhouette of a cow’s head]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSymbolDescription Context triple: [Ferrería/Arena Ciudad de México, hasSymbolDescription, silhouette of a cow’s head]
-
A.
hasDescription
Indicates that an entity is associated with a textual description that explains or characterizes it.
-
B.
symbolDescription
chosen
Indicates that a symbol is associated with or defined by a particular descriptive explanation or meaning.
-
C.
hasSymbolicInterpretation
Indicates that one entity is understood or used as a symbolic representation or metaphorical stand-in for another entity or concept.
-
D.
appearsWithSymbol
Indicates that one entity is shown or presented together with a particular symbol in the same visual or contextual setting.
-
E.
hasSymbolicForm
Indicates that one entity serves as the symbolic representation or abstract form of 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_69d8b9ef17708190bdf7e2adbf14ddc2 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4871f63708190b298ed96896ad0ee |
completed | April 19, 2026, 7:41 a.m. |
| PD | Predicate disambiguation | batch_69e3d8d8e538819084f1584426b41d5e |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:12 a.m.