Triple
T30182095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leonidas 1 |
E767227
|
entity |
| Predicate | hasEntryMethod |
P56178
|
FINISHED |
| Object | rear troop compartment access |
—
|
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: rear troop compartment access | Statement: [Leonidas 1, hasEntryMethod, rear troop compartment access]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEntryMethod Context triple: [Leonidas 1, hasEntryMethod, rear troop compartment access]
-
A.
hasEntryOn
Indicates that one entity contains or includes an entry, record, or listing about another entity.
-
B.
hasEntryExample
Indicates that something includes or is associated with a specific example illustrating one of its entries.
-
C.
hasEntryType
Indicates that something is associated with a specific category or type of entry within a system or dataset.
-
D.
hasEntryFormula
Indicates that something is associated with a specific formula used to represent its entry or defining expression.
-
E.
hasAccessMethod
chosen
Indicates that one entity uses or is associated with a particular method or mechanism for accessing another entity or resource.
- 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_69f2247cc3d88190811dec3face94bf5 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f78c61ed4c8190ad84c918fa9af55a |
completed | May 3, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69f78b8cb3a881909ebaac1b503988c2 |
completed | May 3, 2026, 5:53 p.m. |
Created at: April 29, 2026, 7:26 p.m.