Triple
T821691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roger Staubach |
E17761
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Roger |
E18413
|
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: Roger | Statement: [Roger Staubach, givenName, Roger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roger Context triple: [Roger Staubach, givenName, Roger]
-
A.
Roger
chosen
Roger is a masculine given name of Germanic origin commonly used in English-speaking countries.
-
B.
Robert
Robert is a common masculine given name of Germanic origin, widely used in English-speaking countries.
-
C.
Rob
Rob is a common shortened form of the given name Robert, frequently used as an informal or familiar first name.
-
D.
Ray
Ray is a masculine given name commonly used in English-speaking countries, often as a short form of Raymond.
-
E.
Roy
Roy is a common masculine given name of Celtic origin, often used independently or as a nickname for longer names.
- 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_69a4937bcaac8190a322524ac6f45a5a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab7aea38819092a0860ec6e2a033 |
completed | March 1, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a76d91c2948190bc13a223548facba |
completed | March 3, 2026, 11:24 p.m. |
Created at: March 1, 2026, 7:38 p.m.