Triple
T9240730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sorrentine Coast |
E222051
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Meta |
E443487
|
NE 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: Meta | Statement: [Sorrentine Coast, contains, Meta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meta Context triple: [Sorrentine Coast, contains, Meta]
-
A.
Meta
Meta is a multinational technology company best known as the parent of Facebook, Instagram, and WhatsApp, focusing on social media platforms and virtual/augmented reality technologies.
-
B.
Meta
chosen
Meta is a coastal town on Italy’s Sorrento Peninsula, known for its beaches, cliffs, and proximity to Naples and the Amalfi Coast.
-
C.
Meta
Meta is a figure in Greek mythology known as the first wife of Aegeus, the king of Athens and father of Theseus.
-
D.
Meta
Meta is a discussion section on the Bitcointalk.org forum dedicated to topics about the forum itself, such as its rules, features, feedback, and administration.
-
E.
META
META is a department in central Colombia known for its vast Llanos plains, cattle ranching, and oil production.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca83ee26cc81909ac624e190597d6d |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccf0a3888c8190b72d8d0b850bdfbc |
completed | April 1, 2026, 10:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d077e1ea448190a64a0371a412d314 |
completed | April 4, 2026, 2:30 a.m. |
Created at: March 30, 2026, 7:30 p.m.