Triple
T719402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arthur Geoffrey Walker |
E14382
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Walker |
E30542
|
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: Walker | Statement: [Arthur Geoffrey Walker, familyName, Walker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Walker Context triple: [Arthur Geoffrey Walker, familyName, Walker]
-
A.
Blake
Blake is a given name and surname used in English-speaking countries for people of any gender.
-
B.
Jack
Jack is a common masculine given name, often used as a familiar form of John and widely featured in English-language literature and popular culture.
-
C.
Smith
chosen
Smith is a common English surname borne by numerous notable individuals across diverse fields such as politics, arts, sports, and academia.
-
D.
Wallen
Wallen is the colloquial Dutch name for Amsterdam’s famous Red Light District, known for its historic canals, legalized prostitution, and vibrant nightlife.
-
E.
Tyler
Tyler is the officer in a Masonic lodge responsible for guarding the entrance and ensuring only qualified individuals are admitted to meetings.
- 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_69a4934a36e081909e7abef98b898a4e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a58e65e8819098cba7e6a20d8f33 |
completed | March 1, 2026, 8:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a63759d6108190adcdeac45e4c7766 |
completed | March 3, 2026, 1:20 a.m. |
Created at: March 1, 2026, 7:37 p.m.