Triple
T11114394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Webb Ellis |
E262845
|
entity |
| Predicate | hasLegendStatus |
P1582
|
FINISHED |
| Object | apocryphal origin story of rugby football |
—
|
LITERAL 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: apocryphal origin story of rugby football | Statement: [William Webb Ellis, hasLegendStatus, apocryphal origin story of rugby football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegendStatus Context triple: [William Webb Ellis, hasLegendStatus, apocryphal origin story of rugby football]
-
A.
hasLegendAssociatedWith
chosen
Indicates that something is connected to or accompanied by a traditional story, myth, or legend.
-
B.
hasStatusLabel
Indicates that an entity is associated with a specific status expressed as a human-readable label.
-
C.
hasLegacy
Indicates that an entity leaves behind a lasting impact, influence, or inheritance that continues to exist or be recognized over time.
-
D.
hasLabel
Indicates that an entity is associated with a specific textual label or name used to identify or describe it.
-
E.
hasFlagHistory
Indicates that there exists a historical record or sequence of changes related to an entity’s flag.
- F. None of above.
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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79aa637888190935e852281408356 |
completed | April 9, 2026, 12:25 p.m. |
| PD | Predicate disambiguation | batch_69d7441cf8188190b8095f622c923156 |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:27 p.m.