Triple
T6309278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florence American Cemetery |
E141458
|
entity |
| Predicate | memorialInscriptionsLanguage |
P15804
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Florence American Cemetery, memorialInscriptionsLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memorialInscriptionsLanguage Context triple: [Florence American Cemetery, memorialInscriptionsLanguage, English]
-
A.
inscriptionsLanguage
chosen
Indicates that the language used in the inscriptions on an object or surface is the specified language.
-
B.
hasLanguageOnPlaque
Indicates that a specific language appears in the text or inscription displayed on a particular plaque.
-
C.
officialLanguageOfInscriptions
Indicates the language officially used in the inscriptions associated with a particular entity.
-
D.
bellInscriptionLanguage
Indicates the language in which the inscription on a bell is written.
-
E.
languageOfCommemoration
Indicates the language used to express or perform the act of commemoration.
- 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_69c008d00efc8190a36c05b4b4a3bf4b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0647f13a4819095c4ce8c42c5d1fb |
completed | March 22, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69c060e311b48190b1c74a5cf9435623 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:28 p.m.