Triple
T17172069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philip the Evangelist |
E416758
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Jerusalem |
E6995
|
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: Jerusalem | Statement: [Philip the Evangelist, associatedWith, Jerusalem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jerusalem Context triple: [Philip the Evangelist, associatedWith, Jerusalem]
-
A.
Jerusalem
chosen
Jerusalem is an ancient and historically significant city in the Middle East that serves as a major religious and cultural center for Judaism, Christianity, and Islam.
-
B.
Jerusalem
Jerusalem is a novel by Swedish author Selma Lagerlöf that portrays the lives, faith, and emigration of a group of Swedish villagers who journey to the Holy Land.
-
C.
Jerusalem
Jerusalem is a town in Yates County, New York, known for its rural character and location in the Finger Lakes region.
-
D.
Jerusalén
Jerusalén is a small Bolivian municipality located within the La Paz Department in the Andean region of western Bolivia.
-
E.
Jesusalém
Jesusalém is a novel by Mozambican writer Mia Couto that explores memory, war, and identity through a boy’s life in an isolated, post-conflict African landscape.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3fc0ac22481909e992bb3a6ba36ad |
completed | April 18, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a016745f32c81909499f71920e8babe |
completed | May 11, 2026, 5:21 a.m. |
Created at: April 10, 2026, 5:37 a.m.