Triple
T17100763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Martin de Porres |
E414974
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Martin |
E223140
|
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: Martin | Statement: [Saint Martin de Porres, givenName, Martin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martin Context triple: [Saint Martin de Porres, givenName, Martin]
-
A.
Martin
Martin is the middle name of Henry Martin Tupper, an individual likely known in historical or biographical records.
-
B.
Martin
Martin is the given name of Klaus Martin Einstein, the son of physicist Hans Albert Einstein and grandson of Albert Einstein.
-
C.
Martin
Martin is a central character in the Australian television drama series "The Newsreader," which follows the turbulent personal and professional lives of 1980s newsroom staff.
-
D.
Martin
Martin is the middle name of Roswell Field, an American lawyer best known for his involvement in the Dred Scott case.
-
E.
Martin
chosen
Martin is a masculine given name of Latin origin, commonly used in many European languages.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc0182cc8190b8aa9c980f11ba57 |
completed | April 18, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0139fdda488190a1ca5c7ca875e044 |
completed | May 11, 2026, 2:07 a.m. |
Created at: April 10, 2026, 5:35 a.m.