Triple
T13246475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cross of Sacrifice at Villers-Bretonneux Military Cemetery |
E315417
|
entity |
| Predicate | hasBronzeElement |
P108732
|
FINISHED |
| Object | sword on the face of the cross |
—
|
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: sword on the face of the cross | Statement: [Cross of Sacrifice at Villers-Bretonneux Military Cemetery, hasBronzeElement, sword on the face of the cross]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBronzeElement Context triple: [Cross of Sacrifice at Villers-Bretonneux Military Cemetery, hasBronzeElement, sword on the face of the cross]
-
A.
bronzeMedalist
Indicates that an entity finished third in a competition or event, earning the bronze medal.
-
B.
hasMedalComponent
Indicates that something includes or is composed of a particular medal or medal-related part as one of its components.
-
C.
hasMedalEquivalent
Indicates that one medal is considered equivalent in value, status, or recognition to another medal.
-
D.
numberOfBronzeFigures
Indicates the quantity of bronze figures associated with a given subject or context.
-
E.
hasGoldVault
Indicates that one entity possesses or contains a vault specifically used for storing gold.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d5c09f88190bb1566a6d8c073a6 |
completed | April 10, 2026, 11:53 p.m. |
| PD | Predicate disambiguation | batch_69d98bcca7d88190a3e68e99ed3a29e6 |
completed | April 10, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69d98c959ba08190adf29dc0c4e1fca6 |
completed | April 10, 2026, 11:49 p.m. |
Created at: April 9, 2026, 9:23 p.m.