Triple
T15611206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Weiss |
E375295
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Robert |
E2918
|
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: Robert | Statement: [Robert Weiss, hasGivenName, Robert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robert Context triple: [Robert Weiss, hasGivenName, Robert]
-
A.
Robert
Robert, also known as Rollo, was a Viking leader who became the first ruler of Normandy in the early 10th century.
-
B.
Robert
Robert is a fictional character known primarily for his role in the story of "Betrayal."
-
C.
Robert
Robert is a central character in the British black comedy film "Death at a Funeral," around whom much of the movie’s chaotic and farcical events unfold.
-
D.
Robert
chosen
Robert is a common masculine given name of Germanic origin, widely used in English-speaking countries.
-
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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e8148a0819087d6d69cc84487ca |
completed | April 16, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f3913908190acdd7da62b4f521d |
completed | May 9, 2026, 4:22 p.m. |
Created at: April 10, 2026, 4:13 a.m.