Triple
T4471094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jedermann |
E98495
|
entity |
| Predicate | basedOn |
P98
|
FINISHED |
| Object | Everyman |
E83656
|
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: Everyman | Statement: [Jedermann, basedOn, Everyman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Everyman Context triple: [Jedermann, basedOn, Everyman]
-
A.
Everyman
chosen
Everyman is a stock character archetype representing an ordinary, relatable person placed in extraordinary or challenging situations.
-
B.
Everyman
Everyman is a 2006 short novel by Philip Roth that meditates on aging, illness, and mortality through the life story of an unnamed advertising executive.
-
C.
For Everyman
For Everyman is a 1973 folk-rock album by American singer-songwriter Jackson Browne, noted for its introspective lyrics and reflective, melodic sound.
-
D.
Queen Henrietta's Men
Queen Henrietta's Men was a prominent Caroline-era English playing company active in the 1620s and 1630s, known for performing at the Cockpit Theatre and for its association with Queen Henrietta Maria.
-
E.
The Tailor of Gloucester
The Tailor of Gloucester is a classic children's story by Beatrix Potter about a poor tailor whose work is mysteriously completed by helpful mice on Christmas Eve.
- 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_69b3454b4ae481908967426dd37284d6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b356b6a1f48190a39f5411648c40ff |
completed | March 13, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6377154bc819099362e8b28698dbe |
completed | March 15, 2026, 4:37 a.m. |
Created at: March 12, 2026, 11:35 p.m.