Triple
T38012056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Locksley Hall Sixty Years After |
E948388
|
entity |
| Predicate | hasIntertext |
P52226
|
FINISHED |
| Object | Locksley Hall |
—
|
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: Locksley Hall | Statement: [Locksley Hall Sixty Years After, hasIntertext, Locksley Hall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIntertext Context triple: [Locksley Hall Sixty Years After, hasIntertext, Locksley Hall]
-
A.
intertextualRelation
chosen
Indicates a relationship in which one text references, echoes, or otherwise meaningfully connects to another text.
-
B.
hasIntercalation
Indicates that an entity includes or undergoes the insertion of additional elements (such as units, segments, or periods) into an existing ordered sequence or structure.
-
C.
hasTextualTransmission
Indicates that a work, idea, or content has been passed down, preserved, or conveyed through written or textual forms over time.
-
D.
containsInterpretationOf
Indicates that one entity includes or embodies an interpretation or understanding of another entity.
-
E.
hasTextIn
Indicates that an entity contains or is associated with a specific piece of text within a particular context or location.
- F. None of above.
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_69f76efb4b10819092c8c2ba28ac06a8 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a0141fceb908190863778741bd4487d |
completed | May 11, 2026, 2:42 a.m. |
| PD | Predicate disambiguation | batch_6a0141a9628c819090c0b24ce052a2fb |
completed | May 11, 2026, 2:40 a.m. |
Created at: May 3, 2026, 4:20 p.m.