Triple
T35396216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen Square, Bristol |
E1023083
|
entity |
| Predicate | wasSubsequently |
P182925
|
FINISHED |
| Object | restored in the 19th century |
—
|
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: restored in the 19th century | Statement: [Queen Square, Bristol, wasSubsequently, restored in the 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasSubsequently Context triple: [Queen Square, Bristol, wasSubsequently, restored in the 19th century]
-
A.
wasPrecededBy
Indicates that one event, state, or entity occurred or existed earlier in time than another.
-
B.
wasSecond
Indicates that one entity held the position or rank of second relative to another in a specified order, sequence, or competition.
-
C.
wasA
Indicates that an entity previously had a certain role, type, or classification in the past.
-
D.
subsequentUse
Indicates that one entity is used, applied, or consumed after another entity in time or sequence.
-
E.
wasIn
Indicates that an entity existed, occurred, or was located within a particular place or context during a specified time or situation.
- 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_69f76df34ba48190bd80f0814cdcd540 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79535977881909bc8a562ed19c6d6 |
completed | May 3, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f7910770108190bdd39ddb5d304f54 |
completed | May 3, 2026, 6:16 p.m. |
| PDg | Predicate description generation | batch_69f791cad5e08190a8a04ca283dbecaa |
completed | May 3, 2026, 6:19 p.m. |
Created at: May 3, 2026, 4:03 p.m.