Triple
T7996978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roland Hayes |
E186150
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Roland |
E121395
|
NE 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: Roland | Statement: [Roland Hayes, givenName, Roland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roland Context triple: [Roland Hayes, givenName, Roland]
-
A.
Roland
chosen
Roland is a masculine given name of Germanic origin, historically associated with the legendary Frankish hero of "The Song of Roland" and later borne by various notable figures.
-
B.
Rolland
Rolland is a given name and surname, most commonly recognized as a variant spelling of Roland used in various European and English-speaking contexts.
-
C.
Soult
Soult is a French surname most famously associated with Nicolas Jean-de-Dieu Soult, a prominent marshal of France under Napoleon.
-
D.
Armin
Armin is the given name of Armin Mueller-Stahl, a renowned German actor, painter, and former musician known for his work in both European and Hollywood cinema.
-
E.
Arno
The Arno is a major river in central Italy that flows through cities such as Florence and Pisa before emptying into the Ligurian Sea.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca829c6c308190ab05b43d234c52b2 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c97968481908d261b3f0bd6b8e6 |
completed | March 31, 2026, 3:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc568ac4e88190b63b4d57c3bd3205 |
completed | March 31, 2026, 11:19 p.m. |
Created at: March 30, 2026, 5:17 p.m.