Triple
T13964168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walter Block |
E335878
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Block |
E700158
|
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: Block | Statement: [Walter Block, familyName, Block]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Block Context triple: [Walter Block, familyName, Block]
-
A.
Block
chosen
Block is a surname shared by various notable individuals across fields such as politics, arts, and sciences.
-
B.
Blocks
Blocks is a Python deep learning framework built on top of Theano that provides modular, reusable components for constructing and training neural networks.
-
C.
Blocka
"Blocka" is a hip-hop track by Pusha T known for its dark, aggressive production and hard-edged lyrical style.
-
D.
Blok
Blok is a Russian surname most famously borne by the Symbolist poet Alexander Blok.
-
E.
Block Z
Block Z was the specific spectator section in Brussels’ Heysel Stadium where the fatal crowd crush occurred during the 1985 European Cup final, making it central to the Heysel Stadium disaster.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e7e24f08190ba939a8044860033 |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1d890d48190affd194b2439c271 |
completed | May 6, 2026, 8:17 p.m. |
Created at: April 9, 2026, 10:18 p.m.