Triple
T11997181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Montague |
E285560
|
entity |
| Predicate | hasNoLinesIn |
P85299
|
FINISHED |
| Object | Act 5, Scene 3 (death reported, not shown) |
—
|
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: Act 5, Scene 3 (death reported, not shown) | Statement: [Lady Montague, hasNoLinesIn, Act 5, Scene 3 (death reported, not shown)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoLinesIn Context triple: [Lady Montague, hasNoLinesIn, Act 5, Scene 3 (death reported, not shown)]
-
A.
hasNumberOfLines
Indicates the relationship that specifies how many lines are associated with a given entity.
-
B.
hasNoText
chosen
Indicates that the referenced entity or element contains no textual content.
-
C.
hasLineStructure
Indicates that one entity possesses or exhibits a linear arrangement or organization of its components.
-
D.
hasDeFactoLine
Indicates that there exists an unofficial or non-legally recognized boundary or demarcation line functioning in practice between the related entities.
-
E.
hasLineCharacter
Indicates that one entity possesses or includes a specific character or symbol that appears within a line of text or sequence.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903c172788190b92042e9d10a48bf |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902b245cc8190af96a9c2bd9c6250 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.