Triple
T4543361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meuse-Argonne American Cemetery |
E109988
|
entity |
| Predicate | hasMemorialInscriptionLanguage |
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: [Meuse-Argonne American Cemetery, hasMemorialInscriptionLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMemorialInscriptionLanguage Context triple: [Meuse-Argonne American Cemetery, hasMemorialInscriptionLanguage, English]
-
A.
inscriptionsLanguage
chosen
Indicates that the language used in the inscriptions on an object or surface is the specified language.
-
B.
officialLanguageOfInscriptions
Indicates the language officially used in the inscriptions associated with a particular entity.
-
C.
languageOfHonoredFigure
Indicates the language associated with or used by the person who is being honored.
-
D.
languageOfCommemoration
Indicates the language used to express or perform the act of commemoration.
-
E.
hasNumberOfNamesInscribed
Indicates the quantity of distinct names that are inscribed on a given 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_69bd4412524c8190be5bcc9ddee91848 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57d517e881909c3d23ed4453b0a7 |
completed | March 20, 2026, 2:21 p.m. |
| PD | Predicate disambiguation | batch_69bd5220e40481908ca2d7e2c43d8531 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:05 p.m.