Triple
T13997355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Eligius Hospital |
E336733
|
entity |
| Predicate | hasStaffTypeInStory |
P112091
|
FINISHED |
| Object | attending physicians |
—
|
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: attending physicians | Statement: [St. Eligius Hospital, hasStaffTypeInStory, attending physicians]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStaffTypeInStory Context triple: [St. Eligius Hospital, hasStaffTypeInStory, attending physicians]
-
A.
hasThemeInStory
Indicates that a particular theme is present or plays a significant role within a given story.
-
B.
performedByGroupInStory
Indicates that an action or event within a story is carried out by a group rather than an individual.
-
C.
hasFandomWithinStory
Indicates that within the narrative of a story, one entity is a fan or admirer of another entity (such as a character, group, or work) that exists inside that same story world.
-
D.
hasAwardInStory
Indicates that an entity is depicted within a narrative or story as having received a particular award.
-
E.
hasAllyInStory
Indicates that one entity is portrayed as an ally or supportive partner of another entity within the context of a specific story or narrative.
- F. None of above. chosen
Provenance (4 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_69d81c645c5c8190b1fd16a285a1b78a |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2eb68ba88190bfaf10777d607bf3 |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465dfbc4819090d8c61fd572d35f |
completed | April 13, 2026, 7:39 p.m. |
| PDg | Predicate description generation | batch_69de01ed2098819088ec45069f6f2609 |
completed | April 14, 2026, 8:59 a.m. |
Created at: April 9, 2026, 10:19 p.m.