Triple
T28331612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chopin’s heart at Holy Cross Church, Warsaw |
E717550
|
entity |
| Predicate | hasOuterMonumentMaterial |
P112113
|
FINISHED |
| Object | stone |
—
|
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: stone | Statement: [Chopin’s heart at Holy Cross Church, Warsaw, hasOuterMonumentMaterial, stone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOuterMonumentMaterial Context triple: [Chopin’s heart at Holy Cross Church, Warsaw, hasOuterMonumentMaterial, stone]
-
A.
hasStoneMonument
Indicates that one entity possesses, contains, or features a stone monument associated with it.
-
B.
hasPrimaryMonument
Indicates that an entity is associated with its main or most significant monument.
-
C.
hasArchitecturalMaterial
chosen
Indicates that something is constructed from, incorporates, or is characterized by a particular architectural material.
-
D.
hasMonumentalFeature
Indicates that an entity possesses or includes a significant, large-scale, or historically important physical feature or structure.
-
E.
appliesToMonument
Indicates that something (such as a rule, status, or attribute) is relevant or applicable specifically to a monument.
- 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_69eff6e9a57c8190a69c2c74b5d72119 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f6978fe97081908fe568091ad9b159 |
completed | May 3, 2026, 12:32 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 28, 2026, 12:32 a.m.