Triple
T25107017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seventh Ward of Philadelphia |
E628892
|
entity |
| Predicate | timeOfMostIntenseStudy |
P160100
|
FINISHED |
| Object | 1890s |
—
|
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: 1890s | Statement: [Seventh Ward of Philadelphia, timeOfMostIntenseStudy, 1890s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeOfMostIntenseStudy Context triple: [Seventh Ward of Philadelphia, timeOfMostIntenseStudy, 1890s]
-
A.
studiedDuring
Indicates that an entity engaged in study or academic activity within a specified time period or interval.
-
B.
hasBeenStudiedFor
Indicates that an entity has been the subject of research, examination, or analysis for a specified purpose, topic, or application.
-
C.
hasBeenStudiedSince
Indicates that an entity has been the subject of study or research starting from a specified point in time and continuing thereafter.
-
D.
oftenStudiedBetween
Indicates that something is frequently examined, researched, or analyzed in relation to two or more entities.
-
E.
momentStudy
Indicates a relationship where a specific moment in time is devoted to or characterized by engaging in study or learning activities.
- 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_69e2ff3071548190b62d1ac237397197 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f6018f91248190985323d1a678e539 |
completed | May 2, 2026, 1:52 p.m. |
| PD | Predicate disambiguation | batch_69f5f7f99dc08190afcfb3bc4dfbec1d |
completed | May 2, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69f5ffc6268c8190b63f6360ebadab73 |
completed | May 2, 2026, 1:44 p.m. |
Created at: April 18, 2026, 6:26 a.m.