Triple
T36768882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Treebeard |
E908419
|
entity |
| Predicate | chapterTitleInWhichProminent |
P186278
|
FINISHED |
| Object | Treebeard |
—
|
NE NERFINISHED |
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: Treebeard | Statement: [Treebeard, chapterTitleInWhichProminent, Treebeard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chapterTitleInWhichProminent Context triple: [Treebeard, chapterTitleInWhichProminent, Treebeard]
-
A.
chapterName
Indicates that a chapter is identified or labeled by a specific name or title.
-
B.
chapterMentioned
Indicates that a specific chapter is referenced or cited within a given context or source.
-
C.
chapterOn
Indicates that one entity (typically a chapter) is about, discusses, or focuses on the subject represented by another entity.
-
D.
chapterNameEnglish
Indicates that an entity (such as a chapter) has a specific name expressed in English.
-
E.
chapterNameContext
Indicates the contextual information or surrounding details associated with a chapter’s name within a larger structure or document.
- 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_69f76e786ba481909cdcf6cf6b39dd32 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7cabacc1481909e839454ce1057f7 |
completed | May 3, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69f7c9f4c7c48190ba918d8d5dc8dfd9 |
completed | May 3, 2026, 10:19 p.m. |
Created at: May 3, 2026, 4:12 p.m.