Triple
T20478060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sickla industrial area |
E502371
|
entity |
| Predicate | previousCharacter |
P140242
|
FINISHED |
| Object | industrial |
—
|
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: industrial | Statement: [Sickla industrial area, previousCharacter, industrial]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousCharacter Context triple: [Sickla industrial area, previousCharacter, industrial]
-
A.
previousSymbol
Indicates that one symbol directly precedes another symbol in a defined sequence or ordering.
-
B.
previousRecord
Indicates that one record directly precedes another in an ordered sequence of records.
-
C.
successorCharacter
Indicates that one character directly follows another in a sequence, such as in text, ordering, or narrative progression.
-
D.
currentCharacter
Indicates that an entity is the character presently in focus or being actively considered in a given context or sequence.
-
E.
precedesLetter
Indicates that one letter comes immediately before another letter in a specified ordering, such as the alphabet or a given sequence.
- 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_69e0b4af32848190aea80682b44d5d6e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69966b9748190a5296d8ab03c07a1 |
completed | April 20, 2026, 9:23 p.m. |
| PD | Predicate disambiguation | batch_69e5768372988190b08ef8ae67d42ab6 |
completed | April 20, 2026, 12:42 a.m. |
| PDg | Predicate description generation | batch_69e58d766b408190a1d3698145fb6d30 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:34 a.m.