Triple
T4756351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philip Snowden |
E105596
|
entity |
| Predicate | inOfficeTo |
P58573
|
FINISHED |
| Object | 1924-11-04 |
—
|
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: 1924-11-04 | Statement: [Philip Snowden, inOfficeTo, 1924-11-04]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inOfficeTo Context triple: [Philip Snowden, inOfficeTo, 1924-11-04]
-
A.
inOfficeFrom
Indicates that an entity holds a particular office or position starting from a specified date or time.
-
B.
officeIsIn
Indicates that one office is located within or inside another specified place or building.
-
C.
otherOffice
Indicates that one office is an alternative or additional office associated with the same organization, person, or entity as another office.
-
D.
office
Indicates that an entity holds or occupies an official position, role, or post within an organization or institution.
-
E.
officeItAbbreviatesLeads
Indicates that an office-related IT abbreviation serves as or corresponds to the leading part or primary form of another term or designation.
- 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_69bd43f14cac819081c7c69803648211 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64e9d80c819088532921a46ea1d6 |
completed | March 20, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69bd6223defc8190823665a6592c1154 |
completed | March 20, 2026, 3:05 p.m. |
| PDg | Predicate description generation | batch_69bd6424a1d08190ac1d5fc574dc1b55 |
completed | March 20, 2026, 3:13 p.m. |
Created at: March 20, 2026, 1:20 p.m.