Triple
T2131887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iron Cross |
E46558
|
entity |
| Predicate | inscriptionFeature |
P34998
|
FINISHED |
| Object | year of institution on lower arm |
—
|
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: year of institution on lower arm | Statement: [Iron Cross, inscriptionFeature, year of institution on lower arm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inscriptionFeature Context triple: [Iron Cross, inscriptionFeature, year of institution on lower arm]
-
A.
inscriptionType
Indicates the specific kind or category of inscription associated with an entity (e.g., dedicatory, funerary, commemorative).
-
B.
inscriptionSource
Indicates the origin or source from which an inscription was derived, created, or obtained.
-
C.
inscriptionBy
Indicates that an inscription was created, written, or carved by a particular agent or entity.
-
D.
inscription
Indicates that text has been written, carved, or engraved onto a surface or object.
-
E.
inscriptionIncludesLine
Indicates that an inscription contains a specific line of text as one of its components.
- 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_69a88a1626548190ae59a5028c3baa8e |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbb7b13ac819094d43159fff984cf |
completed | March 7, 2026, 5:45 a.m. |
| PD | Predicate disambiguation | batch_69abb7bf56e481909b0f497d238451cc |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb860a51c8190b4ae3bb1cedc0fa0 |
completed | March 7, 2026, 5:32 a.m. |
Created at: March 4, 2026, 7:44 p.m.